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. 2014 Nov 12;9(11):e112980. doi: 10.1371/journal.pone.0112980

Table 2. Performance of classification of CXRs dataset, DB using various feature extraction methods.

Feature* Accuracy Sensitivity Specificity Precision F-score GMean AUC CI# SE#
Gab1 0.920 0.920 0.920 0.920 0.920 0.920 0.936 0.829–0.986 0.0377
Gist1 0.860 0.880 0.840 0.846 0.863 0.860 0.893 0.773–0.962 0.0520
HOG1 0.860 0.800 0.920 0.909 0.851 0.858 0.909 0.793–0.972 0.0434
PHOG1 0.900 0.920 0.880 0.885 0.902 0.900 0.918 0.806–0.977 0.0404

*Features extracted from: 1 indicates whole CXR, 2 indicates manually segmented CXR and 3 indicates automatic segmented CXR.

#

CI refers to confidence interval at 95% at P-value <0.0001 whereas SE refers to standard error for AUC.